When developing a treatment plan for cervical cancer, it is important to be able to determine a patients prognosis, ideally at the time of diagnosis. Existing methods to arrive at a prognosis can be time consuming, inaccurate and may require specialized software. Therefore, doctors from the Washington University School of Medicine developed – and validated – an accurate, reproducible and quick prognostic system.
The researchers created a grading scale to use in conjunction with a simple visual analysis of 18F-FDG PET scans. The grading system considered the size and shape of the primary tumor, as well as the heterogeneity of 18F-FDG uptake and presence of lymph nodes. A cutoff value was established to separate the women with "good" and "bad" prognoses, and Kaplan-Meier analysis provided a guideline both for progression-free survival and for overall survival. Researchers also examined whether knowledge about the presence of lymph notes impacted the efficacy of the system.
The retrospective study was conducted using data from 47 patients. Three independent observers, who had no knowledge of the patients, evaluated and graded the PET scans. The close scores and survival prognoses of the three observers demonstrated the reproducibility of the test. A comparison of the observers projected outcomes and the actual outcomes verified the accuracy and the power of this visual analysis; for example, 80% of those women who were predicted to have a bad diagnosis did not survive while only 10% with a good prognosis died. The information about the presence of lymph nodes increased the accuracy only slightly compared to the analysis of tumor characteristics alone.
Kimberly A. Bennett | EurekAlert!
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